diff --git a/lib/nnc/mfa/ccv_nnc_mfa_attention.cpp b/lib/nnc/mfa/ccv_nnc_mfa_attention.cpp
index 87ebb9c4e..0e602cbdc 100644
--- a/lib/nnc/mfa/ccv_nnc_mfa_attention.cpp
+++ b/lib/nnc/mfa/ccv_nnc_mfa_attention.cpp
@@ -98,11 +98,11 @@ void ccv_nnc_mfa_encode_attention(mfa::context* context, ccv_nnc_mfa_attention_p
       pool->drain();
       auto kernel = pipelineValue->kernel;
       auto pipeline = pipelineValue->pipeline;
-        // Allocate a new command.
+      // Allocate a new command.
       auto encoder = command_batch->startCommand();
       encoder->setComputePipelineState(pipeline.get());
       encoder->setThreadgroupMemoryLength(kernel->threadgroupMemoryAllocation, 0);
-    
+
       // Bind the function arguments.
       encoder->useResource(tensors[0], MTL::ResourceUsageRead);
       encoder->useResource(tensors[1], MTL::ResourceUsageRead);
@@ -146,17 +146,37 @@ void ccv_nnc_mfa_encode_attention(mfa::context* context, ccv_nnc_mfa_attention_p
           encoder->setBuffer(scratch, 0, AttentionOperand(AttentionOperand::L).bufferIndex());
         }
       }
-    
+
       MTL::Size gridSize
-      (ceilDivide(int64_t(hash.R), kernel->blockDimensions[0]),
-       hash.Hq,
-       attentionDesc.batchDimension);
+      (ceilDivide(int64_t(hash.R), kernel->blockDimensions[0]), 1, 1);
       MTL::Size groupSize
       (int64_t(kernel->threadgroupSize), 1, 1);
-    
-      // Dispatch the required number of threads.
-      encoder->dispatchThreadgroups(gridSize, groupSize);
-    
+
+      const size_t bytesPerElement = attentionDesc.lowPrecisionInputs ? sizeof(uint16_t) : sizeof(float);
+      for (int i = 0; i < attentionDesc.batchDimension; i++) {
+        for (int j = 0; j < hash.Hq; j++) {
+          encoder->setBufferOffset(tensor_offsets[0] + bytesPerElement * (i * hash.R * hash.D * hash.Hq + j * hash.D), AttentionOperand(AttentionOperand::Q).bufferIndex());
+          encoder->setBufferOffset(tensor_offsets[1] + bytesPerElement * (i * hash.C * hash.D * hash.Hk + j * hash.D), AttentionOperand(AttentionOperand::K).bufferIndex());
+          encoder->setBufferOffset(tensor_offsets[2] + bytesPerElement * (i * hash.C * hash.D * hash.Hk + j * hash.D), AttentionOperand(AttentionOperand::V).bufferIndex());
+          if (attentionDesc.lowPrecisionInputs) {
+            encoder->setBufferOffset(sizeof(float) * (i * hash.R * hash.D * hash.Hq + j * hash.D), AttentionOperand(AttentionOperand::O).bufferIndex());
+            if (tensors[5]) {
+              encoder->setBufferOffset(tensor_offsets[5] + sizeof(float) * (i * hash.R * hash.Hq + j * hash.R), AttentionOperand(AttentionOperand::L).bufferIndex());
+            } else {
+              encoder->setBufferOffset(sizeof(float) * hash.R * hash.D * hash.Hq * attentionDesc.batchDimension + sizeof(float) * (i * hash.R * hash.Hq + j * hash.R), AttentionOperand(AttentionOperand::L).bufferIndex());
+            }
+          } else {
+            encoder->setBufferOffset(tensor_offsets[3] + sizeof(float) * (i * hash.R * hash.D * hash.Hq + j * hash.D), AttentionOperand(AttentionOperand::O).bufferIndex());
+            if (tensors[5]) {
+              encoder->setBufferOffset(tensor_offsets[5] + sizeof(float) * (i * hash.R * hash.Hq + j * hash.R), AttentionOperand(AttentionOperand::L).bufferIndex());
+            } else {
+              encoder->setBufferOffset(sizeof(float) * (i * hash.R * hash.Hq + j * hash.R), AttentionOperand(AttentionOperand::L).bufferIndex());
+            }
+          }
+          // Dispatch the required number of threads.
+          encoder->dispatchThreadgroups(gridSize, groupSize);
+        }
+      }
       // Finish the command.
       command_batch->finishCommand(encoder);
       if (attentionDesc.lowPrecisionInputs) {
diff --git a/lib/nnc/mfa/v2/AttentionKernel.cpp b/lib/nnc/mfa/v2/AttentionKernel.cpp
index fe749b509..64cecbef0 100644
--- a/lib/nnc/mfa/v2/AttentionKernel.cpp
+++ b/lib/nnc/mfa/v2/AttentionKernel.cpp
@@ -520,7 +520,11 @@ std::string AttentionKernel::operandLocationWithHeadOffsetValue(AttentionOperand
   CodeWriter source;
   source.SetValue("OPERAND", operand.name());
   if (operand.value == AttentionOperand::L || operand.value == AttentionOperand::D) {
-    source += "{{OPERAND}} + (gid.z * Hq + gid.y) * R\\";
+    if (Hq > 1) {
+      source += "{{OPERAND}} + (gid.z * Hq + gid.y) * R\\";
+    } else {
+      source += "{{OPERAND}} + gid.z * R\\";
+    }
   } else if (Hq > 1) {
     source.SetValue("HEAD_DIMENSION", std::to_string(headDimension));
     if (!transposed(operand)) {